Optimal Distributed Energy Resource Management System

ABSTRACT

A method comprises generating power at a solar photovoltaic cell; receiving, at a controller, one or more input parameters pertaining to a power output of the solar photovoltaic cell; introducing liquid to the solar photovoltaic cell in response to the power output of the solar photovoltaic cell to increase the efficiency of the solar photovoltaic cell; recovering heat from the liquid introduced to the solar photovoltaic cell; and selecting an appropriate distribution of the power output of the solar photovoltaic cell to one or more power-drawing components in a way that maximizes a chosen objective for the whole of system.

BACKGROUND

The exemplary embodiments of this invention relate generally to energyresource management systems and, more specifically, to the managementand control of components in a solar photovoltaic system.

Solar photovoltaic (PV) technology is a fast-growing form of energygeneration. Many users have been able to obtain higher returns fromsolar PV systems via incremental improvements, for example, improvementsin solar panel materials or manufacturing processes by which the solarpanels are fabricated.

However, solar PV material is only one component in an overall system ofgenerating and using energy. A typical system of generating and usingenergy based on solar PV technology generally lacks a holistic controlsystem that manages energy generation and consumption in an optimalmanner. In particular, systems used to control the generation and use ofenergy based on solar PV technology generally do not account forenvironmental factors (such as reduction of solar PV system output dueto external temperature or panel soiling), local pricing structures, oradditional components that affect energy generation and use (e.g.,cooling systems, stationary storage, electric vehicles, and the like).

BRIEF SUMMARY

In one exemplary aspect, a method comprises generating power at a solarphotovoltaic cell; receiving, at a controller, one or more inputparameters pertaining to a power output of the solar photovoltaic cell;introducing liquid cooling and cleaning to the solar photovoltaic cellin response to the power output of the solar photovoltaic cell toincrease the efficiency of the solar photovoltaic cell; recovering heatfrom the liquid introduced to the solar photovoltaic cell; and selectingan appropriate distribution of the power output of the photovoltaic cellto one or more power-drawing components.

In another exemplary aspect, a system for managing the distribution ofenergy among multiple components comprises a solar photovoltaicgeneration system configured to generate power; an energy storagesystem; a cold storage system; a heat bank; an end user; and a computerthat controls operations of the solar photovoltaic generation system,wherein the computer is configured to receive one or more inputparameters pertaining to a power output of the solar photovoltaicgeneration system and one or more input parameters pertaining to powerrequirements of the energy storage system, the cold storage system, theheat bank, and the end user; wherein the computer is configured to causethe introduction of liquid to the solar photovoltaic generation systemin response to the power output of the solar photovoltaic generationsystem to increase the efficiency of the solar photovoltaic generationsystem; and wherein the computer is configured to select an appropriatedistribution of the power output of the solar photovoltaic cell to oneor more of the energy storage system, the cold storage system, the heatbank, and the end user to achieve a user-defined objective.

In another exemplary aspect, a computer program product for managing thedistribution of energy among multiple components comprises a computerreadable storage medium having program instructions embodied therewith,the program instructions being executable by a computer to cause thecomputer to: receive one or more input parameters pertaining to a poweroutput of a solar photovoltaic cell; cause liquid to be introduced tothe solar photovoltaic cell in response to the power output of the solarphotovoltaic cell to increase the efficiency of the solar photovoltaiccell; and select an appropriate distribution of power outputs to one ormore power-drawing components.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The foregoing and other aspects of exemplary embodiments are made moreevident in the following Detailed Description, when read in conjunctionwith the attached Drawing Figures, wherein:

FIG. 1 is a block diagram illustrating one exemplary embodiment of ahigh level process for optimally distributing energy resources;

FIG. 2 is a block diagram illustrating one exemplary embodiment of aniteration of the optimal distribution of FIG. 1;

FIG. 3 is a block diagram illustrating another exemplary embodiment of awhole-of-system approach to distributing energy resources in a solar PVsystem;

FIG. 4 is a block diagram illustrating another exemplary embodiment of awhole-of-system approach to distributing energy resources in a solar PVsystem;

FIG. 5 is a block diagram illustrating one exemplary approach to theoptimal management and control of the generation of power, energystorage components, and cold storage components;

FIG. 6 is a block diagram of a controller for use with the approach ofFIG. 5;

FIG. 7 is a schematic illustration of operation mode constraints of thecontroller of FIG. 6;

FIG. 8 is a block diagram of one exemplary embodiment of electronicdevices that are suitable for use in the embodiments described herein;and

FIG. 9 is a graphical representation of electricity price and usage overthe course of a day.

DETAILED DESCRIPTION

Referring to FIG. 1, one exemplary embodiment of a high level processfor optimally distributing energy resources is shown generally at 100and is hereinafter referred to as “process 100.” In process 100, anInternet of Things (IoT) 110 may be used to collect data, the data beingprovided as an output 115 to an analytics module 120, which analyzes thedata and provides outputs 125 to one or more of an optimization module130, a user interaction and feedback module 140, and an optimizationfrequency module 150. Outputs 160 from the optimization module 130 mayalso be communicated to the user interaction and feedback module 140 andto the optimization frequency module 150. Feedback 165 may be receivedfrom the user interaction and feedback module 140 at the optimizationmodule 130. An output 170 from the optimization frequency module 150,may be returned back to the IoT 110.

The IoT 110 may collect any immediately available data including, butnot limited to, temperatures of solar panels, amount of soiling (dirt)on solar panels, air temperature, humidity, electricity price, batteryinformation relating to charge levels, cold storage charge levels,electric vehicle (EV) state of charge, numbers of people present in abuilding, and the like. As used herein, cold storage charge levels maybe temperatures reached by a given amount of cold storage medium (e.g.,a refrigerant), an amount of solid ice generated as part of a freezingprocess, or the like.

The analytics module 120 may, for example, generate further data. Suchdata includes, but is not limited to, forecast information (e.g.,demand, generation, weather, price, and the like). Other data generatedby the analytics module 120 may include, but is not limited to,estimated states of sub-systems to which energy resources are optimallydistributed (e.g., expected occupancies of buildings, expected EVdemands, expected thermal fluctuations, and the like). The analyticsmodule 120 may also identify the amount of dispatchable demand. As usedherein, dispatchable demand may be any demand that can be time-shifted.Exemplary dispatchable demands include, but are not limited to, washingmachines, dish washers, electric vehicle chargers, and the like, whichcan be scheduled to charge overnight (when electricity prices are lowdue to low demand) instead of during the day. In the alternative, suchdevices may be scheduled to charge in the middle of the day (forexample, during peak sunlight hours when solar PV generation is high).

In the optimization module 130, a ranked list of value propositions maybe generated. The generated ranked list may be based on optimal use ofresources and/or user-defined priorities. Value propositions mayinclude, but are not limited to, solar PV generation boost using coldstorage, solar PV generation boost via liquid cooling (and cleaning),solar self-consumption, beneficial grid export, optimal energy flowwithin a building, and the like.

The user interaction and feedback module 140 may be Cloud-based and mayinclude dashboarding (graphical presentation of a report to a user inreal time).

The optimization frequency module 150 may optimize the valuepropositions from the optimization module 130 based on time. Theoptimized value propositions may then be returned to the IoT 110. Forexample, data collected pertinent to the temperatures of the solarpanels may be used to determine that the solar panels are operating atan inefficient temperature, which may lead to initiation of a coolingprocess. Alternatively, a determination that the solar panels are soiledmay lead to an initiation of a cleaning process. In some cases bothcooling and cleaning may be conducted simultaneously, for example usingliquid (e.g., water) sprayed onto or running over the solar panels.

Referring now to FIG. 2, a flow illustrating one iteration of onepossible embodiment of the optimal distribution of FIG. 1 from an IoTlevel 220 through an analytics level 230 and down to an optimizationlevel 240 is shown generally at 200 and is hereinafter referred to as“optimization 200.” In optimization 200, a user may desire to minimizesupport (e.g., input power) from a power grid. External inputs 210 tothe IoT level 220 include, but are not limited to, environmental data(e.g., temperature, humidity, soiling levels, sky images, and the like),PV system data (e.g., power output, desired temperatures, and the like),cold storage data (e.g., temperatures, fill levels of refrigerants (forexample), and the like), energy storage data (e.g., state of charge),and external data (e.g., price of electricity).

At the analytics level 230, occupancy forecasts may be generated (e.g.,numbers of people in a building at specified times). Other forecasts mayalso be generated (e.g., personal electricity demand, expected solar PVgeneration, weather, and the like). Furthermore, estimates may be madepertaining to changes in thermal mass as well as load requirements andidentifications as to what portions of the total expected load may bedispatchable (and can be shifted if necessary).

At the optimization level 240, various queries 250 are made withsubsequent decisions 260 being rendered. For example, queries 250 maypertain to whether solar PV production should be boosted, whether coldstorage should be increased, whether dispatchable loads should be run,etc. Decisions 260 rendered may relate to using cold storage for panelcooling, boosting cold storage levels, running dispatchable loads, etc.

Referring to FIG. 3, one exemplary embodiment of a whole-of-systemapproach to distributing energy resources in a solar PV systemassociated with a building is shown generally at 300 and is hereinafterreferred to as “distribution 300.” In the distribution 300, cells ofsolar panels may be used to generate power for any desired building use.Water may be introduced to the solar panels as indicated in block 310.The water may be poured, sprayed, misted, trickled, or otherwiseintroduced to the solar panels. The water may be clean water (e.g.,building tap water). As an alternative or in addition to clean water,water from another source such as collected rainwater or graywater maybe used. As shown in block 320, the cells of the solar panels may becleaned and cooled by the water, thus increasing the efficiency of thecells. The water, which recovers heat from the solar panels, may becollected as indicated in block 330. The heated water may be filtered ifneeded as indicated in block 340. The heated water may then be reused,for example, in a hot water system, in a heat bank, or for any otherbuilding purpose as indicated in block 350.

Referring to FIG. 4, another exemplary embodiment of a whole-of-systemapproach to distributing energy resources in a solar PV systemassociated with a building is shown generally at 400 and is hereinafterreferred to as “distribution 400.” In the distribution 400, power output410 from a panel 415 of a solar PV system can be used to provide cooling(e.g., for refrigeration or air conditioning) to a cold storage 420.Operation of the solar PV system can also be boosted 425 by the coldstorage 420 (e.g., cooling can be returned to the cells of the panel 415to boost efficiency at times when increased solar PV generation isdesired). The cold storage 420 can also be cooled using a power output430 of a power grid 435. A building 440 (e.g., house, commercialbuilding, factory, or the like) may be powered by one or both of thepower output 410 from the panel 415 and the power output 430 from thepower grid 435. The building, may also be cooled by a cooling stream 450from the cold storage 420. In doing so, cost savings may be realized bythe use of the power output 410 from the panels 415 to cool the coldstorage 420 with the use of excess power from the cold storage 420. Thisdual use both cools the building 440 and boosts PV generation at thepanel 415 (e.g., by about 10%) when needed most. Thus, there is nolow-value export of energy back to the power grid 435, and there is botha reduction in demand from the power grid 435 and an increase in powergeneration at times of peak power draw.

Referring now to FIG. 5, a holistic approach to optimal management andcontrol of the generation of power, energy storage components, andthermal storage components using a controller is shown generally at 500and is referred to as “system 500.” System 500 may use the controller(shown at 600) to control operation of a solar PV generation apparatus510 and further to operate power-drawing components of the system 500 inan optimal manner according to a desired operation mode.

System 500 is a user-defined environment that comprises the solar PVgeneration apparatus 510 (e.g., comprising panels 415) configured toprovide power output 515 to one or more power-drawing components orsub-systems such as, for example, a system for cold storage 520, asystem for energy storage 525, and a building 550. As indicated herein,the solar PV generation apparatus 510 may, based on data collectedpertaining to power output of the solar PV generation apparatus 510,introduce liquid to the solar PV generation apparatus 510 to cool and/orclean the cells of the panels, thereby increasing the efficiency of thesolar PV generation apparatus 510. Furthermore, any heat recovered fromthe cooling and/or cleaning may be either applied to one or morecomponents of the system (e.g., as heat to the building 550) or storedin a heat bank 517 for subsequent use in one or more components of thesystem.

The cold storage 520 may comprise a refrigeration or air conditioningsystem driven by the power output 515 from the solar PV generationapparatus 510. Furthermore, the energy storage 525 may comprise anysuitable energy storage apparatus, e.g., a battery bank, an electricvehicle, or the like, to which the power output 515 from the solar PVgeneration apparatus 510 provides power. The energy storage 525 may beconfigured to provide outputs 540 to the cold storage 520 and thebuilding 550. The energy storage 525 may be further configured toexchange power 555 with a power grid 535. The power grid 535 may providean output 580 to the cold storage 520 and/or to the building 550, whichmay have a temperature demand 560 and an electrical energy demand 565.The cold storage 520 may be configured to provide an output as anefficiency boost 570 back to the solar PV generation apparatus 510 bycooling the solar PV generation apparatus 510 and also to provide anoutput 575 as cooling to the building 550. The controller 600 may beconfigured to control various aspects of the cold storage 520, theenergy storage 525, the building 550, and the solar PV generationapparatus 510 to manage the optimal distribution of energy resources.

Referring now to FIG. 6, the controller 600 is configured to distributethe power generated by the solar PV apparatus 510 as well as the coolingand/or cleaning of the panels of the solar PV apparatus 510 and anyfurther use of the resulting (possibly heated) liquid. The controller600 is also configured to receive a plurality of input parametersincluding, but not limited to, electricity price 610, information fromsensors 620, forecasts 630, system-specific information 640, operationmode constraints 650, and any other available information. Such inputsmay be used by the controller 600, in conjunction with the controlledgenerated power from the solar PV apparatus 510, to make optimal systemdecisions at discrete intervals. In doing so, the controller 600 selectsappropriate distributions of the available outputs to the power-drawingcomponents such as the cold storage 520, the energy storage 525, and thepower grid 535. The optimal system decisions and the appropriatelyselected distributions of output 660 may be displayed on a graphicaluser interface (GUI 670).

With regard to the inputs to the controller 600 (which may be a “smart”controller), an algorithm that seeks to optimize the user-definedenvironment may be employed. Thus, the controller 600 is more than asimple thermostat since it integrates several datasets based on theinput parameters (the forecasts 630 such as weather forecasts, thesystem-specific information, and the like).

The sensors 620 may receive information such as temperature inside thebuilding 550 (which may be multiple temperatures taken at variouspoints), temperature of the cell surface of the panels 415 of the solarPV apparatus 510, temperature of the cold storage 520, and the like. Forsensed temperatures inside the building that are above a specifiedsetpoint, the controller 600 may direct the cold storage 520 to provideadditional cooling to the building 550. For sensed temperatures, insidethe building that are below a specified setpoint, the controller 600 maydirect the building 550 (e.g., via the temperature demand 560) to drawheat from the heat bank 517. The sensors 620 may also receiveinformation such as external air temperatures, battery storage levels,indications of power produced by the solar PV apparatus 510, the numberof people in the building 550 at different times, and the like. Anindication of the power produced by the solar PV apparatus 510 may beused to estimate the extent of soiling of the panels 415 (e.g., how muchdirt has accumulated), thus causing the appropriate liquid to bedirected to the solar PV apparatus 510 for cleaning.

The forecasts 630 received into the controller 600 may includeinformation relating to the amount of predicted sun (or cloud cover),predicted temperature/weather, and predicted energy usage. With regardto predicted energy usage, a dataset may be compiled over time, such adataset being indicative of past usage patterns and containing all therelevant measurements for predicting future energy consumption patterns.Machine-learning methods may enable the accuracy of such predictions tocontinually improve over time.

System-specific information 640 that may be input into the controller600 includes, for example, tariff structure and battery degradationrates as well as configuration parameters for each of the systemcomponents. Such configuration parameters may be related to the cells ofthe panels 415 of the solar PV apparatus 510, inverters, batteries, andthe cold storage 520 (e.g., air conditioning, refrigeration, otherbuilding cooling mechanisms). For each system component, variousrelevant parameters may be stored in a memory. For example, a batterysystem may need to specify battery capacity, charge/discharge rates,preferred charge levels, efficiencies at various levels, degradation ofthe batteries, and the like.

Referring now to FIG. 7, exemplary embodiments of the operation modeconstraints 650 are shown. Each operation mode constraint 650 may beselectable via touch controls on the GUI 670. Various operation modeconstraints 650 include those configured to: take advantage of energyoutput based on frequency of power outages (e.g., selecting mode 710 mayconfigure the system to always have a battery charged to 60%); takeadvantage of cost savings (e.g., selecting mode 720 may configure thesystem to save as much money on energy as possible, possibly by drawingand storing grid power during off-peak times); promote grid independence(e.g., selecting mode 730 to use as little grid power as possible); seta vacation mode 740 (e.g., to sell as much power as possible back to thepower grid 535); and set a commercial or industrial mode 750 (e.g., toavoid surpassing a peak demand level at all times).

At different times, a user may desire different operating modes. Asimplified GUI 670 may allow the user to define their overall goals,with the underlying details of the configurations of the modeconstraints 650 being generally hidden. A Cloud-based GUI may also allowthe user to control and monitor their particular system remotely.

Referring now to FIG. 8, a simplified block diagram of variouselectronic devices and apparatuses that are suitable for use inpracticing the exemplary embodiments described herein is shown. Forexample, a computer 800 may be used to control one or more of theprocesses as described above. The computer 800 includes a controller(e.g., controller 600) which has a data processor (DP) 814 and acomputer-readable memory medium embodied as a memory (MEM) 816 thatstores a program of computer instructions (PROG) 818.

The PROG 818 includes program instructions that, when executed by theassociated DP 814, enable the various electronic devices and apparatusesto operate in accordance with exemplary embodiments. That is, variousexemplary embodiments may be implemented at least in part by computersoftware executable by the DP 814 of the computer 800, or by hardware,or by a combination of software and hardware (and firmware).

The computer 800 may also include dedicated processors, for example aprocessor 815 that manipulates data pertaining to the input parametersto initiate cooling and/or cleaning at the solar PV apparatus 510 and todistribute power in an optimal manner.

The computer readable MEM 816 may be of any type suitable to the localtechnical environment and may be implemented using any suitable datastorage technology, such as semiconductor based memory devices, flashmemory, magnetic memory devices and systems, optical memory devices andsystems, fixed memory, and removable memory. The DP 814 may be of anytype suitable to the local technical environment, and may include one ormore of general purpose computers, special purpose computers,microprocessors, digital signal processors (DSPs), and processors basedon a multicore processor architecture, as non-limiting examples.

The exemplary embodiments, as discussed herein and as particularlydescribed with respect to exemplary methods, may be implemented inconjunction with a program storage device (e.g., at least one memory)readable by a machine, tangibly embodying a program of instructions(e.g., a program or computer program) executable by the machine forperforming operations. The operations comprise utilizing the exemplaryembodiments of the methods described herein.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network, and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers, and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer, or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowcharts and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowcharts or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

In one exemplary embodiment, a method comprises generating power at asolar photovoltaic cell; receiving, at a controller, one or more inputparameters pertaining to a power output of the solar photovoltaic cell;introducing liquid cooling and cleaning to the solar photovoltaic cellin response to the power output of the solar photovoltaic cell toincrease the efficiency of the solar photovoltaic cell; recovering heatfrom the liquid introduced to the solar photovoltaic cell; and selectingan appropriate distribution of the power output of the photovoltaic cellto one or more power-drawing components.

The method may further comprise storing the recovered heat from theliquid introduced to the solar photovoltaic cell. The method may furthercomprise causing the solar photovoltaic cell to exchange power with apower grid. The method may further comprise estimating an amount ofsoiling on the solar photovoltaic cell in response to receiving one ormore input parameters pertaining to a power output of the solarphotovoltaic cell. Receiving one or more input parameters pertaining toa power output of the solar photovoltaic cell may comprise receiving oneor more of information from a sensor, information from a forecast,information specific to the solar photovoltaic cell, and informationfrom an operation mode constraint. Introducing liquid to the solarphotovoltaic cell may comprise one or more of pouring, spraying,misting, and trickling liquid on the solar photovoltaic cell. The methodmay further comprise filtering the liquid after recovery of the heatfrom the liquid. Selecting an appropriate distribution of the output ofthe solar photovoltaic cell to one or more power-drawing components maycomprise distributing outputs to one or more of a cold storage system,an energy storage system, and a building. One of the system componentsmay be a stationary or mobile energy storage system that can be chargedby one or both of the solar photovoltaic cell and the power grid, anddischarge to one or more of a building, the power grid, and a coldstorage system. One of the system components may be a cold storagesystem that may receive energy from one or more of the solarphotovoltaic cell, the power grid, and the energy storage system, andprovide cooling to one or both of the solar photovoltaic system and abuilding.

In another exemplary embodiment, a system for managing the distributionof energy among multiple components comprises a solar photovoltaicgeneration system configured to generate power; an energy storagesystem; a cold storage system; a heat bank; an end user; and a computerthat controls operations of the solar photovoltaic generation system,wherein the computer is configured to receive one or more inputparameters pertaining to a power output of the solar photovoltaicgeneration system and one or more input parameters pertaining to powerrequirements of the energy storage system, the cold storage system, theheat bank, and the end user; wherein the computer is configured to causethe introduction of liquid to the solar photovoltaic generation systemin response to the power output of the solar photovoltaic generationsystem to increase the efficiency of the solar photovoltaic generationsystem; and wherein the computer is configured to select an appropriatedistribution of the power output of the solar photovoltaic cell to oneor more of the energy storage system, the cold storage system, the heatbank, and the end user to achieve a user-defined objective.

In the system, the computer may be further configured to cause the solarphotovoltaic generation system to exchange power with a power grid. Thecomputer may be further configured to estimate an amount of soiling on asolar photovoltaic cell of the solar photovoltaic generation system inresponse to receiving one or more input parameters pertaining to a poweroutput of the solar photovoltaic generation system. The computerconfigured to receive one or more input parameters pertaining to a poweroutput of the solar photovoltaic generation system may comprisereceiving one or more of information from a sensor, information from aforecast, information specific to the solar photovoltaic cell, andinformation from an operation mode constraint. The computer configuredto cause the introduction of liquid to the solar photovoltaic cell maycomprise one or more of pouring, spraying, misting, and trickling liquidon the solar photovoltaic cell. The computer configured to select anappropriate distribution of the power output of the solar photovoltaicgeneration system to one or more power-drawing components may comprisedistributing outputs to one or more of a cold storage system, an energystorage system, and a building.

In another exemplary embodiment, a computer program product for managingthe distribution of energy among multiple components comprises acomputer readable storage medium having program instructions embodiedtherewith, the program instructions being executable by a computer tocause the computer to: receive one or more input parameters pertainingto a power output of a solar photovoltaic cell; cause liquid to beintroduced to the solar photovoltaic cell in response to the poweroutput of the solar photovoltaic cell to increase the efficiency of thesolar photovoltaic cell; and select an appropriate distribution of poweroutputs to one or more power-drawing components.

The computer program product may further comprise causing the computerto initiate an exchange of power between the solar photovoltaic cell anda power grid. The computer program product may further comprise causingthe computer to estimate an amount of soiling on the solar photovoltaiccell in response to receiving one or more input parameters pertaining toa power output of the solar photovoltaic cell. Causing the computer toselect an appropriate distribution of power outputs to one or morepower-drawing components may comprise causing the computer to distributeoutputs to one or more of a cold storage system, an energy storagesystem, and a building.

Example 1

Referring back to FIG. 3, in one example of the incorporation of thedistribution 300 into a building at a particular location, an increasedvalue was realized by the cooling aspect of the water. In particular, ona hot day, up to about a 20% increase in the generation of heat wasrealized. Additionally, on a warm day, about an 11% increase in thegeneration of heat was realized. Furthermore, over an average 145 daysummer drought, soiling resulted in a 7.4% loss in efficiency. The lossin efficiency due to soiling was determined to be more than an order ofmagnitude larger than losses due to degradation of cells in solar panelsin the solar PV system installed. Variations were noted in otherlocations. Moreover, with regard to the cost of water and filtration,rainwater was collected at no cost, and tap water was used at a smallcost (and no pumping cost). The filtration of rainwater, even aftercleaning of the solar panels, was commonplace and not expensive.

Example 2

Referring now to FIG. 9, in one example of a case study involving anidealized power demand profile averaged over a plurality of users,electricity price and usage over the course of a typical day is showngenerally by graph 900. As can be seen by the graph 900, electricityprice per kilowatt hour (kWh) (shown at 905) from a power grid was about$0.20 through the early morning hours (off-peak time 910 during whichdraw from the power grid was minimal), after which the price doubled andremained constant until about mid-evening hours (peak usage time 920during which draw from the power grid was heavy). After the peak usagetime 920, the price per kWh returned to about $0.20.

Over part of this cycle, electricity was produced by system 500. Theelectricity produced could be fed back to the power grid at a feed-intariff 925 of $0.05 per kWh. However, given that import of energy was atleast $0.20/kWh (during off-peak hours) and $0.40/kWh (during peakhours), feeding back to the grid represented a loss of value at alltimes.

Looking at power generation and demand profiles 927 over time, sincegeneration 930 by the system 500 occurred during daylight hours but apeak demand 940 was somewhat later, a differential was observed betweenexport and import tariffs (export exceeded import from about 9:00 AM toabout 4:00 PM, after which draw from the power grid was greater thangeneration by the system 500). Thus, every kWh of solar PV power thatwas not self-consumed occurred between about 9:00 AM to about 4:00 PM.If this excess generation could have been stored locally to offset later(peak) energy use, each kWh shifted would save $0.40/kWh whilerepresenting a lost feed-in tariff opportunity of $0.05/kWh, for a netvalue gain of $0.35 per kWh.

At the same time, with lower costs for energy overnight ($0.20) andhigher costs during the day ($0.40) there was another price differential(of $0.20) that could be taken advantage of in terms of tariffoptimization—charging, an energy storage system overnight anddischarging during the day.

An energy storage system in this embodiment therefore would need totrade off two possible value streams against one another, withmaximization of solar self-consumption (at $0.35/kWh) as the mostattractive option, but tariff optimization ($0.20/kWh) as an additionalimportant value stream.

In some instances, excessive generation may lead to high voltages in thepower grid, which may in turn lead to curtailment of electricity beinggenerated by solar PV systems. Therefore, it may be desirable to shiftthe peak demand 940 as much as possible to the time period of optimalgeneration 930, or to store excess generation during optimal generation930.

The foregoing description has provided by way of exemplary andnon-limiting examples a full and informative description of the bestmethods, systems, and apparatuses presently contemplated by theinventors for carrying out various exemplary embodiments. However,various modifications and adaptations may become apparent to thoseskilled in the relevant arts in view of the foregoing description, whenread in conjunction with the accompanying drawings and the appendedclaims. However, all such and similar modifications will still fallwithin the scope of the teachings of the exemplary embodiments.

Furthermore, some of the features of the preferred embodiments could beused to advantage without the corresponding use of other features. Assuch, the foregoing description should be considered as merelyillustrative of the principles, and not in limitation thereof.

What is claimed is:
 1. A method, comprising: generating power at a solarphotovoltaic cell; receiving, at a controller, one or more inputparameters pertaining to a power output of the solar photovoltaic cell;introducing liquid cooling and cleaning to the solar photovoltaic cellin response to the power output of the solar photovoltaic cell toincrease the efficiency of the solar photovoltaic cell; recovering heatfrom the liquid introduced to the solar photovoltaic cell; and selectingan appropriate distribution of the power output of the photovoltaic cellto one or more power-drawing components.
 2. The method of claim 1,further comprising storing the recovered heat from the liquid introducedto the solar photovoltaic cell.
 3. The method of claim 1, furthercomprising causing the solar photovoltaic cell to exchange power with apower grid.
 4. The method of claim 1, further comprising estimating anamount of soiling on the solar photovoltaic cell in response toreceiving one or more input parameters pertaining to a power output ofthe solar photovoltaic cell.
 5. The method of claim 1, wherein receivingone or more input parameters pertaining to a power output of the solarphotovoltaic cell comprises receiving one or more of information from asensor, information from a forecast, information specific to the solarphotovoltaic cell, and information from an operation mode constraint. 6.The method of claim 1, wherein introducing liquid to the solarphotovoltaic cell comprises one or more of pouring, spraying, misting,and trickling liquid on the solar photovoltaic cell.
 7. The method ofclaim 1, further comprising filtering the liquid after recovery of theheat from the liquid.
 8. The method of claim 1, wherein selecting anappropriate distribution of the power output of the solar photovoltaiccell to one or more power-drawing components comprises distributingoutputs to one or more of a cold storage system, an energy storagesystem, and a building.
 9. The method of claim 8, wherein one of thesystem components is a stationary or mobile energy storage system thatcan be charged by one or both of the solar photovoltaic cell and thepower grid, and discharge to one or more of a building, the power grid,and a cold storage system.
 10. The method of claim 8, wherein one of thesystem components is a cold storage system that may receive energy fromone or more of the solar photovoltaic cell, the power grid, and theenergy storage system, and provide cooling to one or both of the solarphotovoltaic system and a building.
 11. A system for managing thedistribution of energy among multiple components, the system comprising:a solar photovoltaic generation system configured to generate power; anenergy storage system; a cold storage system; a heat bank; an end user;and a computer that controls operations of the solar photovoltaicgeneration system; wherein the computer is configured to receive one ormore input parameters pertaining to a power output of the solarphotovoltaic generation system and one or more input parameterspertaining to power requirements of the energy storage system, the coldstorage system, the heat bank, and the end user; wherein the computer isconfigured to cause the introduction of liquid to the solar photovoltaicgeneration system in response to the power output of the solarphotovoltaic generation system to increase the efficiency of the solarphotovoltaic generation system; and wherein the computer is configuredto select an appropriate distribution of the power output of the solarphotovoltaic cell to one or more of the energy storage system, the coldstorage system, the heat bank, and the end user to achieve auser-defined objective.
 12. The system of claim 11, wherein the computeris further configured to cause the solar photovoltaic generation systemto exchange power with a power grid.
 13. The system of claim 11, whereinthe computer is further configured to estimate an amount of soiling on asolar photovoltaic cell of the solar photovoltaic generation system inresponse to receiving one or more input parameters pertaining to a poweroutput of the solar photovoltaic generation system.
 14. The system ofclaim 11, wherein the computer configured to receive one or more inputparameters pertaining to a power output of the solar photovoltaicgeneration system comprises receiving one or more of information from asensor, information from a forecast, information specific to the solarphotovoltaic cell, and information from an operation mode constraint.15. The system of claim 11, wherein the computer configured to cause theintroduction of liquid to the solar photovoltaic cell comprises one ormore of pouring, spraying, misting, and trickling liquid on the solarphotovoltaic cell.
 16. The system of claim 11, wherein the computerconfigured to select an appropriate distribution of the power output ofthe solar photovoltaic generation system to one or more power-drawingcomponents comprises distributing outputs to one or more of a coldstorage system, an energy storage system, and a building.
 17. A computerprogram product for managing the distribution of energy among multiplecomponents, the computer program product comprising a computer readablestorage medium having program instructions embodied therewith, theprogram instructions being executable by a computer to cause thecomputer to: receive one or more input parameters pertaining to a poweroutput of a solar photovoltaic cell; cause liquid to be introduced tothe solar photovoltaic cell in response to the power output of the solarphotovoltaic cell to increase the efficiency of the solar photovoltaiccell; and select an appropriate distribution of power outputs to one ormore power-drawing components.
 18. The computer program product of claim17, further comprising causing the computer to initiate an exchange ofpower between the solar photovoltaic cell and a power grid.
 19. Thecomputer program product of claim 17, further comprising causing thecomputer to estimate an amount of soiling on the solar photovoltaic cellin response to receiving one or more input parameters pertaining to apower output of the solar photovoltaic cell.
 20. The computer programproduct of claim 17, wherein causing the computer to select anappropriate distribution of power outputs to one or more power-drawingcomponents comprises causing the computer to distribute outputs to oneor more of a cold storage system, an energy storage system, and abuilding.